{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 布林带策略逻辑：\n",
    "\n",
    "1. CCI指标（60分钟趋势过滤）\n",
    "2. 布林通道（15分钟波动信号）\n",
    "3. ATR指标（15分钟吊灯Stop止损单）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from __future__ import division\n",
    "\n",
    "from vnpy.trader.vtObject import VtBarData\n",
    "from vnpy.trader.vtConstant import EMPTY_STRING\n",
    "from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate, \n",
    "                                                     BarGenerator, \n",
    "                                                     ArrayManager)\n",
    "import talib as ta\n",
    "\n",
    "########################################################################\n",
    "class BollChannelStrategy(CtaTemplate):\n",
    "    \"\"\"基于布林通道的交易策略\"\"\"\n",
    "    className = 'BollChannelStrategy'\n",
    "    author = u'用Python的交易员'\n",
    "\n",
    "    # 策略交易标的的列表\n",
    "    symbolList = []         # 初始化为空\n",
    "    posDict = {}  # 初始化仓位字典\n",
    "\n",
    "    # 多空仓位\n",
    "    Longpos = EMPTY_STRING        # 多头品种仓位\n",
    "    Shortpos = EMPTY_STRING       # 空头品种仓位\n",
    "\n",
    "    # 策略参数\n",
    "    bollWindow = 20                      # 布林通道窗口数\n",
    "    bollDev = 4                         # 布林通道的偏差\n",
    "    cciWindow = 20                      # CCI窗口数\n",
    "    atrWindow = 25                      # ATR窗口数\n",
    "    slMultipler = 3                    # 计算止损距离的乘数\n",
    "    initDays = 2                        # 初始化数据所用的天数\n",
    "    fixedSize = 100                       # 每次交易的数量\n",
    "\n",
    "    # 策略变量\n",
    "    intraTradeHigh = 0                  # 持仓期内的最高点\n",
    "    intraTradeLow = 0                   # 持仓期内的最低点\n",
    "    longStop = 0                        # 多头止损\n",
    "    shortStop = 0                       # 空头止损\n",
    "    Trend = 0\n",
    "    \n",
    "    # 参数列表，保存了参数的名称\n",
    "    paramList = ['name',\n",
    "                 'className',\n",
    "                 'author',\n",
    "                 'symbolList',\n",
    "                 'bollWindow',\n",
    "                 'bollDev',\n",
    "                 'cciWindow',\n",
    "                 'atrWindow',\n",
    "                 'slMultiplier',\n",
    "                 'initDays',\n",
    "                 'fixedSize']    \n",
    "\n",
    "    # 变量列表，保存了变量的名称\n",
    "    varList = ['inited',\n",
    "               'trading',\n",
    "               'posDict',\n",
    "               'bollUp',\n",
    "               'bollDown',\n",
    "               'cciValue',\n",
    "               'atrValue',\n",
    "               'intraTradeHigh',\n",
    "               'intraTradeLow',\n",
    "               'longStop',\n",
    "               'shortStop',\n",
    "               'Trend']  \n",
    "    \n",
    "    # 同步列表，保存了需要保存到数据库的变量名称\n",
    "    syncList = ['posDict',\n",
    "                'intraTradeHigh',\n",
    "                'intraTradeLow']    \n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def __init__(self, ctaEngine, setting):\n",
    "        \"\"\"Constructor\"\"\"\n",
    "        super(BollChannelStrategy, self).__init__(ctaEngine, setting)\n",
    "        \n",
    "        # 生成仓位记录的字典\n",
    "        symbol = self.symbolList[0]\n",
    "        self.Longpos = symbol.replace('.','_')+\"_LONG\"\n",
    "        self.Shortpos = symbol.replace('.','_')+\"_SHORT\"\n",
    "        \n",
    "        self.bg15Dict = {\n",
    "            sym: BarGenerator(self.onBar, 15, self.on15minBar)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "        \n",
    "        self.bg60Dict = {\n",
    "            sym: BarGenerator(self.onBar, 60, self.on60minBar)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "        \n",
    "        \n",
    "        self.am15Dict = {\n",
    "            sym: ArrayManager(size=self.bollWindow*2)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "        \n",
    "        self.am60Dict = {\n",
    "            sym: ArrayManager(size=self.cciWindow*2)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "        \n",
    "        self.intraTradeHighDict = {}\n",
    "        self.intraTradeLowDict = {}\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onInit(self):\n",
    "        \"\"\"初始化策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略初始化' %self.name)\n",
    "        self.ctaEngine.initPosition(self)\n",
    "        # 载入历史数据，并采用回放计算的方式初始化策略数值\n",
    "        initData = self.loadBar(self.initDays)\n",
    "        for bar in initData:\n",
    "            self.onBar(bar)\n",
    "\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStart(self):\n",
    "        \"\"\"启动策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略启动' %self.name)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStop(self):\n",
    "        \"\"\"停止策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略停止' %self.name)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onTick(self, tick):\n",
    "        \"\"\"收到行情TICK推送（必须由用户继承实现）\"\"\" \n",
    "        self.bgDict[tick.vtSymbol].updateTick(tick)\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onBar(self, bar):\n",
    "        \"\"\"收到Bar推送（必须由用户继承实现）\"\"\"\n",
    "        symbol = bar.vtSymbol\n",
    "        bg15 = self.bg15Dict[symbol]\n",
    "        bg15.updateBar(bar)\n",
    "        \n",
    "        bg60 = self.bg60Dict[symbol]\n",
    "        bg60.updateBar(bar)\n",
    "    \n",
    "    #----------------------------------------------------------------------\n",
    "    def on60minBar(self, bar):\n",
    "        symbol = bar.vtSymbol\n",
    "\n",
    "        # 保存K线数据\n",
    "        am60 = self.am60Dict[symbol]\n",
    "        am60.updateBar(bar)\n",
    "        \n",
    "        if not am60.inited:\n",
    "            return\n",
    "        \n",
    "        cciValue = am60.cci(self.cciWindow)\n",
    "        if cciValue > 0:\n",
    "            self.Trend = 1\n",
    "        if cciValue < 0:\n",
    "            self.Trend = -1\n",
    "        \n",
    "    def on15minBar(self, bar):\n",
    "        symbol = bar.vtSymbol\n",
    "\n",
    "        # 保存K线数据\n",
    "        am15 = self.am15Dict[symbol]\n",
    "        am15.updateBar(bar)\n",
    "        \n",
    "        if not am15.inited:\n",
    "            return\n",
    "        # 计算指标数值\n",
    "        bollUp, bollMean ,bollDown = ta.BBANDS(am15.close, self.bollWindow, self.bollDev)\n",
    "        atrValue = ta.ATR(am15.high, am15.low, am15.close, self.atrWindow)\n",
    "        \n",
    "#         判断是否要进行交易\n",
    "#         当前无仓位，发送开仓委托\n",
    "        if self.posDict[self.Longpos] == 0 and self.posDict[self.Shortpos] == 0:\n",
    "            self.intraTradeHighDict[symbol] = 0\n",
    "            self.intraTradeLowDict[symbol] = 999999\n",
    "            if self.Trend==1:\n",
    "                if am15.close[-1]>=bollUp[-1] and am15.close[-2]<=bollUp[-2]:\n",
    "                    self.buy(symbol, bar.close*1.1 , self.fixedSize)\n",
    "            elif self.Trend==-1:\n",
    "                if am15.close[-1]<=bollUp[-1] and am15.close[-2]>=bollUp[-2]:\n",
    "                    self.short(symbol, bar.close*0.9, self.fixedSize)\n",
    "\n",
    "        # 持有多头仓位\n",
    "        elif self.posDict[self.Longpos] >0:\n",
    "            self.intraTradeHighDict[symbol] = max(self.intraTradeHighDict[symbol], bar.high)\n",
    "            self.intraTradeLowDict[symbol] = bar.low\n",
    "            self.longStop = self.intraTradeHighDict[symbol] - atrValue[-1] * self.slMultipler\n",
    "            self.cancelAll()\n",
    "            self.sell(symbol, self.longStop, self.posDict[self.Longpos], True) # 发送Stop单\n",
    "\n",
    "#         # 持有空头仓位\n",
    "        elif self.posDict[self.Shortpos] > 0:\n",
    "            self.intraTradeHighDict[symbol] = bar.high\n",
    "            self.intraTradeLowDict[symbol] = min(self.intraTradeLowDict[symbol], bar.low)\n",
    "            self.shortStop = self.intraTradeLowDict[symbol] + atrValue[-1] * self.slMultipler\n",
    "            self.cancelAll()\n",
    "            self.cover(symbol, self.shortStop, self.posDict[self.Shortpos], True) # 发送Stop单\n",
    "        \n",
    "        self.saveSyncData()        \n",
    "        # 发出状态更新事件\n",
    "        self.putEvent()        \n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onOrder(self, order):\n",
    "        \"\"\"收到委托变化推送（必须由用户继承实现）\"\"\"\n",
    "        pass\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onTrade(self, trade):\n",
    "#         print(self.posDict)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStopOrder(self, so):\n",
    "        \"\"\"停止单推送\"\"\"\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def runBacktesting(strategyClass, settingDict, \n",
    "                   startDate, endDate, slippage, \n",
    "                   rate, size, priceTick):\n",
    "    \"\"\"运行单标的回测\"\"\"\n",
    "    engine = BacktestingEngine()\n",
    "    engine.setBacktestingMode(engine.BAR_MODE)\n",
    "    engine.setDatabase(MINUTE_DB_NAME)\n",
    "    engine.setStartDate(startDate, initDays=1)\n",
    "    engine.setEndDate(endDate)\n",
    "    engine.setSlippage(slippage)\n",
    "    engine.setRate(rate)   \n",
    "    engine.setSize(size)         \n",
    "    engine.setPriceTick(priceTick)\n",
    "    engine.initStrategy(strategyClass, settingDict)\n",
    "    engine.setCapital(100000)\n",
    "    engine.runBacktesting()\n",
    "\n",
    "    #显示逐日回测结果\n",
    "    engine.showDailyResult()\n",
    "    #显示逐笔回测结果\n",
    "    engine.showBacktestingResult()\n",
    "    # 计算回测结果\n",
    "    df = engine.calculateDailyResult()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:04.914186\t开始回测\n",
      "2018-07-14 14:49:04.914186\t策略初始化\n",
      "2018-07-14 14:49:04.914186\t载入历史数据。数据范围:[20171231,20180101)\n",
      "2018-07-14 14:49:05.077021\t载入完成，数据量：1414\n",
      "2018-07-14 14:49:05.087009\t策略初始化完成\n",
      "2018-07-14 14:49:05.087009\t策略启动完成\n",
      "2018-07-14 14:49:05.088007\t开始回放回测数据,回测范围:[20180101,20180701)\n",
      "2018-07-14 14:49:05.088007\t载入历史数据。数据范围:[20180101,20180311)\n",
      "2018-07-14 14:49:13.551367\t载入完成，数据量：99357\n",
      "2018-07-14 14:49:13.552367\t当前回放数据:[20180101,20180311)\n",
      "2018-07-14 14:49:14.915974\t载入历史数据。数据范围:[20180311,20180519)\n",
      "2018-07-14 14:49:23.193523\t载入完成，数据量：99073\n",
      "2018-07-14 14:49:23.229486\t当前回放数据:[20180311,20180519)\n",
      "2018-07-14 14:49:24.465225\t载入历史数据。数据范围:[20180519,20180701)\n",
      "2018-07-14 14:49:29.492093\t载入完成，数据量：61359\n",
      "2018-07-14 14:49:29.533051\t当前回放数据:[20180519,20180701)\n",
      "2018-07-14 14:49:30.350217\t数据回放结束ss: 100%    \n",
      "2018-07-14 14:49:30.351215\t计算按日统计结果\n",
      "2018-07-14 14:49:30.371195\t------------------------------\n",
      "2018-07-14 14:49:30.371195\t首个交易日：\t2018-01-01\n",
      "2018-07-14 14:49:30.371195\t最后交易日：\t2018-06-30\n",
      "2018-07-14 14:49:30.371195\t总交易日：\t181\n",
      "2018-07-14 14:49:30.371195\t盈利交易日\t5\n",
      "2018-07-14 14:49:30.371195\t亏损交易日：\t6\n",
      "2018-07-14 14:49:30.371195\t起始资金：\t100000\n",
      "2018-07-14 14:49:30.371195\t结束资金：\t138,982.25\n",
      "2018-07-14 14:49:30.371195\t总收益率：\t38.98%\n",
      "2018-07-14 14:49:30.371195\t年化收益：\t51.69%\n",
      "2018-07-14 14:49:30.371195\t总盈亏：\t38,982.25\n",
      "2018-07-14 14:49:30.371195\t最大回撤: \t-9,353.66\n",
      "2018-07-14 14:49:30.371195\t百分比最大回撤: -6.7%\n",
      "2018-07-14 14:49:30.371195\t总手续费：\t16,987.75\n",
      "2018-07-14 14:49:30.371195\t总滑点：\t440.0\n",
      "2018-07-14 14:49:30.371195\t总成交金额：\t16,987,750.0\n",
      "2018-07-14 14:49:30.371195\t总成交笔数：\t22\n",
      "2018-07-14 14:49:30.371195\t日均盈亏：\t215.37\n",
      "2018-07-14 14:49:30.371195\t日均手续费：\t93.85\n",
      "2018-07-14 14:49:30.371195\t日均滑点：\t2.43\n",
      "2018-07-14 14:49:30.371195\t日均成交金额：\t93,854.97\n",
      "2018-07-14 14:49:30.371195\t日均成交笔数：\t0.12\n",
      "2018-07-14 14:49:30.371195\t日均收益率：\t0.18%\n",
      "2018-07-14 14:49:30.371195\t收益标准差：\t1.74%\n",
      "2018-07-14 14:49:30.371195\tSharpe Ratio：\t1.62\n"
     ]
    },
    {
     "data": {
      "image/png": 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8nPXr19Pc3ExeXh5jxoxh9erVpKamYrPZ2LhxI2VlZSxatIjFixdTUlJCcnIy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      "text/plain": [
       "<matplotlib.figure.Figure at 0x183b636deb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:32.073457\t计算回测结果\n",
      "2018-07-14 14:49:32.075455\t------------------------------\n",
      "2018-07-14 14:49:32.075455\t第一笔交易：\t2018-02-27 16:16:00\n",
      "2018-07-14 14:49:32.075455\t最后一笔交易：\t2018-06-30 06:46:00\n",
      "2018-07-14 14:49:32.075455\t总交易次数：\t11\n",
      "2018-07-14 14:49:32.075455\t总盈亏：\t38,982.25\n",
      "2018-07-14 14:49:32.075455\t最大回撤: \t-9,353.66\n",
      "2018-07-14 14:49:32.075455\t平均每笔盈利：\t3,543.84\n",
      "2018-07-14 14:49:32.075455\t平均每笔滑点：\t40.0\n",
      "2018-07-14 14:49:32.075455\t平均每笔佣金：\t1,544.34\n",
      "2018-07-14 14:49:32.075455\t胜率\t\t45.45%\n",
      "2018-07-14 14:49:32.075455\t盈利交易平均值\t9,900.84\n",
      "2018-07-14 14:49:32.075455\t亏损交易平均值\t-1,753.66\n",
      "2018-07-14 14:49:32.075455\t盈亏比：\t5.65\n"
     ]
    },
    {
     "data": {
      "image/png": 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atNH999+vdevWqWPHjr5qBkLFu+9K/fqZXQUAAAhAJwzEn3/++Qm/+PLLL//F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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x183bd176630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:32.858655\t计算按日统计结果\n"
     ]
    }
   ],
   "source": [
    "if __name__==\"__main__\":\n",
    "    from vnpy.trader.app.ctaStrategy.ctaBacktesting import BacktestingEngine, OptimizationSetting, MINUTE_DB_NAME\n",
    "\n",
    "    bollDf = runBacktesting(BollChannelStrategy, {'symbolList':['tBTCUSD:bitfinex']} , '20180101', '20180630', 0.2, 1/1000, 1, 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ATR_RSI策略逻辑\n",
    "1. ATR>maAtr: 波动放大\n",
    "2. RSI>50+rsiEntry, 趋势向上 买入\n",
    "3. RSI<50-rsiEntry, 趋势向下 卖出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from __future__ import division\n",
    "\n",
    "from vnpy.trader.vtObject import VtBarData\n",
    "from vnpy.trader.vtConstant import EMPTY_STRING\n",
    "from vnpy.trader.app.ctaStrategy.ctaTemplate import (CtaTemplate, \n",
    "                                                     BarGenerator, \n",
    "                                                     ArrayManager)\n",
    "import talib as ta\n",
    "\n",
    "########################################################################\n",
    "class AtrRsiStrategy(CtaTemplate):\n",
    "    \"\"\"基于布林通道的交易策略\"\"\"\n",
    "    className = 'AtrRsiStrategy'\n",
    "    author = u'用Python的交易员'\n",
    "\n",
    "    # 策略交易标的的列表\n",
    "    symbolList = []         # 初始化为空\n",
    "    posDict = {}  # 初始化仓位字典\n",
    "\n",
    "    # 多空仓位\n",
    "    Longpos = EMPTY_STRING        # 多头品种仓位\n",
    "    Shortpos = EMPTY_STRING       # 空头品种仓位\n",
    "\n",
    "    # 策略参数\n",
    "    atrLength = 40        # 计算ATR指标的窗口数   \n",
    "    atrMaLength = 40       # 计算ATR均线的窗口数\n",
    "    rsiLength = 40        # 计算RSI的窗口数\n",
    "    rsiEntry = 10         # RSI的开仓信号\n",
    "    trailingPercent = 0.4  # 百分比移动止损\n",
    "    initDays = 1           # 初始化数据所用的天数\n",
    "    fixedSize = 1           # 每次交易的数量\n",
    "    \n",
    "    \n",
    "    # 策略变量\n",
    "    atrValue = 0                        # 最新的ATR指标数值\n",
    "    atrMa = 0                           # ATR移动平均的数值\n",
    "    rsiValue = 0                        # RSI指标的数值\n",
    "    rsiBuy = 0                          # RSI买开阈值\n",
    "    rsiSell = 0                         # RSI卖开阈值\n",
    "    intraTradeHigh = 0                  # 移动止损用的持仓期内最高价\n",
    "    intraTradeLow = 0                   # 移动止损用的持仓期内最低价\n",
    "    \n",
    "    # 参数列表，保存了参数的名称\n",
    "    paramList = ['name',\n",
    "                 'className',\n",
    "                 'author',\n",
    "                 'symbolList',\n",
    "                 'atrLength',\n",
    "                 'atrMaLength',\n",
    "                 'rsiLength',\n",
    "                 'rsiEntry',\n",
    "                 'trailingPercent']    \n",
    "\n",
    "    # 变量列表，保存了变量的名称\n",
    "    varList = ['inited',\n",
    "               'trading',\n",
    "               'posDict',\n",
    "               'atrValue',\n",
    "               'atrMa',\n",
    "               'rsiValue',\n",
    "               'rsiBuy',\n",
    "               'rsiSell']  \n",
    "    \n",
    "    # 同步列表，保存了需要保存到数据库的变量名称\n",
    "    syncList = ['posDict',\n",
    "                'intraTradeHigh',\n",
    "                'intraTradeLow']    \n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def __init__(self, ctaEngine, setting):\n",
    "        \"\"\"Constructor\"\"\"\n",
    "        super(AtrRsiStrategy, self).__init__(ctaEngine, setting)\n",
    "        \n",
    "        # 生成仓位记录的字典\n",
    "        symbol = self.symbolList[0]\n",
    "        self.Longpos = symbol.replace('.','_')+\"_LONG\"\n",
    "        self.Shortpos = symbol.replace('.','_')+\"_SHORT\"\n",
    "        \n",
    "        self.bg15Dict = {\n",
    "            sym: BarGenerator(self.onBar, 15, self.on15minBar)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "        \n",
    "        self.am15Dict = {\n",
    "            sym: ArrayManager(size=self.atrLength*3)\n",
    "            for sym in self.symbolList\n",
    "        }\n",
    "       \n",
    "        self.intraTradeHighDict = {}\n",
    "        self.intraTradeLowDict = {}\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onInit(self):\n",
    "        \"\"\"初始化策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略初始化' %self.name)\n",
    "        self.ctaEngine.initPosition(self)\n",
    "        \n",
    "        # 初始化RSI入场阈值\n",
    "        self.rsiBuy = 50 + self.rsiEntry\n",
    "        self.rsiSell = 50 - self.rsiEntry\n",
    "        \n",
    "        # 载入历史数据，并采用回放计算的方式初始化策略数值\n",
    "        initData = self.loadBar(self.initDays)\n",
    "        for bar in initData:\n",
    "            self.onBar(bar)\n",
    "\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStart(self):\n",
    "        \"\"\"启动策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略启动' %self.name)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStop(self):\n",
    "        \"\"\"停止策略（必须由用户继承实现）\"\"\"\n",
    "        self.writeCtaLog(u'%s策略停止' %self.name)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onTick(self, tick):\n",
    "        \"\"\"收到行情TICK推送（必须由用户继承实现）\"\"\" \n",
    "        self.bgDict[tick.vtSymbol].updateTick(tick)\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onBar(self, bar):\n",
    "        \"\"\"收到Bar推送（必须由用户继承实现）\"\"\"\n",
    "        symbol = bar.vtSymbol\n",
    "        bg15 = self.bg15Dict[symbol]\n",
    "        bg15.updateBar(bar)\n",
    "        \n",
    "    def on15minBar(self, bar):\n",
    "        symbol = bar.vtSymbol\n",
    "\n",
    "        # 建立数组-----------------------------------------------------------------\n",
    "        am15 = self.am15Dict[symbol]\n",
    "        am15.updateBar(bar)\n",
    "        \n",
    "        if not am15.inited:\n",
    "            return\n",
    "        # 计算指标数组-------------------------------------------------------------\n",
    "        atr = ta.ATR(am15.high, am15.low, am15.close, self.atrLength)\n",
    "        atrMa = ta.MA(atr, self.atrMaLength)\n",
    "        rsiValue = ta.RSI(am15.close, self.rsiLength)\n",
    "        \n",
    "        # 进出场信号---------------------------------------------------------------\n",
    "        if self.posDict[self.Longpos] == 0 and self.posDict[self.Shortpos] == 0:\n",
    "            self.intraTradeHighDict[symbol] = bar.high\n",
    "            self.intraTradeLowDict[symbol] = bar.low\n",
    "            if atr[-1] >= atrMa[-1] and atr[-2] <= atrMa[-2]:\n",
    "                if rsiValue[-1] > self.rsiBuy:\n",
    "                    self.buy(symbol, bar.close+1, self.fixedSize)\n",
    "            elif atr[-1] <= atrMa[-1] and atr[-2] >= atrMa[-2]:\n",
    "                if rsiValue[-1] < self.rsiSell:\n",
    "                    self.short(symbol, bar.close-1, self.fixedSize)\n",
    "                    \n",
    "\n",
    "        # 持有多头仓位\n",
    "        elif self.posDict[self.Longpos] >0:\n",
    "            self.intraTradeHighDict[symbol] = max(self.intraTradeHighDict[symbol], bar.high)\n",
    "            self.intraTradeLowDict[symbol] = bar.low\n",
    "            longStop =  self.intraTradeHighDict[symbol] * (1-self.trailingPercent/100)\n",
    "            self.cancelAll()\n",
    "            self.sell(symbol, longStop, self.posDict[self.Longpos], True)\n",
    "\n",
    "#         # 持有空头仓位\n",
    "        elif self.posDict[self.Shortpos] > 0:\n",
    "            self.intraTradeHighDict[symbol] = bar.high\n",
    "            self.intraTradeLowDict[symbol] = min(self.intraTradeLowDict[symbol], bar.low)\n",
    "            shortStop = self.intraTradeLowDict[symbol] * (1+self.trailingPercent/100)\n",
    "            self.cancelAll()\n",
    "            self.cover(symbol, shortStop, self.posDict[self.Shortpos], True)\n",
    "\n",
    "        self.saveSyncData()        \n",
    "        # 发出状态更新事件\n",
    "        self.putEvent()        \n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onOrder(self, order):\n",
    "        \"\"\"收到委托变化推送（必须由用户继承实现）\"\"\"\n",
    "        pass\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onTrade(self, trade):\n",
    "        # 发出状态更新事件\n",
    "        print(self.posDict)\n",
    "        self.putEvent()\n",
    "\n",
    "    #----------------------------------------------------------------------\n",
    "    def onStopOrder(self, so):\n",
    "        \"\"\"停止单推送\"\"\"\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:33.122386\t开始回测\n",
      "2018-07-14 14:49:33.122386\t策略初始化\n",
      "2018-07-14 14:49:33.122386\t载入历史数据。数据范围:[20171231,20180101)\n",
      "2018-07-14 14:49:33.260244\t载入完成，数据量：1414\n",
      "2018-07-14 14:49:33.277228\t策略初始化完成\n",
      "2018-07-14 14:49:33.278227\t策略启动完成\n",
      "2018-07-14 14:49:33.278227\t开始回放回测数据,回测范围:[20180101,20180701)\n",
      "2018-07-14 14:49:33.279226\t载入历史数据。数据范围:[20180101,20180311)\n",
      "2018-07-14 14:49:41.411924\t载入完成，数据量：99357\n",
      "2018-07-14 14:49:41.411924\t当前回放数据:[20180101,20180311)\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "2018-07-14 14:49:42.412900\t载入历史数据。数据范围:[20180311,20180519)\n",
      "2018-07-14 14:49:50.353793\t载入完成，数据量：99073\n",
      "2018-07-14 14:49:50.389757\t当前回放数据:[20180311,20180519)\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "2018-07-14 14:49:51.394730\t载入历史数据。数据范围:[20180519,20180701)\n",
      "2018-07-14 14:49:56.356664\t载入完成，数据量：61359\n",
      "2018-07-14 14:49:56.391630\t当前回放数据:[20180519,20180701)\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 1}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 1, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "{'tBTCUSD:bitfinex_LONG': 0, 'tBTCUSD:bitfinex_SHORT': 0}\n",
      "2018-07-14 14:49:57.186816\t数据回放结束ss: 100%    \n",
      "2018-07-14 14:49:57.186816\t计算按日统计结果\n",
      "2018-07-14 14:49:57.208794\t------------------------------\n",
      "2018-07-14 14:49:57.208794\t首个交易日：\t2018-01-01\n",
      "2018-07-14 14:49:57.208794\t最后交易日：\t2018-06-30\n",
      "2018-07-14 14:49:57.208794\t总交易日：\t181\n",
      "2018-07-14 14:49:57.208794\t盈利交易日\t30\n",
      "2018-07-14 14:49:57.208794\t亏损交易日：\t32\n",
      "2018-07-14 14:49:57.208794\t起始资金：\t100000\n",
      "2018-07-14 14:49:57.208794\t结束资金：\t101,194.52\n",
      "2018-07-14 14:49:57.208794\t总收益率：\t1.19%\n",
      "2018-07-14 14:49:57.208794\t年化收益：\t1.58%\n",
      "2018-07-14 14:49:57.208794\t总盈亏：\t1,194.52\n",
      "2018-07-14 14:49:57.208794\t最大回撤: \t-681.28\n",
      "2018-07-14 14:49:57.208794\t百分比最大回撤: -0.67%\n",
      "2018-07-14 14:49:57.208794\t总手续费：\t1,464.97\n",
      "2018-07-14 14:49:57.208794\t总滑点：\t31.6\n",
      "2018-07-14 14:49:57.208794\t总成交金额：\t1,464,966.54\n",
      "2018-07-14 14:49:57.208794\t总成交笔数：\t158\n",
      "2018-07-14 14:49:57.208794\t日均盈亏：\t6.6\n",
      "2018-07-14 14:49:57.208794\t日均手续费：\t8.09\n",
      "2018-07-14 14:49:57.208794\t日均滑点：\t0.17\n",
      "2018-07-14 14:49:57.208794\t日均成交金额：\t8,093.74\n",
      "2018-07-14 14:49:57.208794\t日均成交笔数：\t0.87\n",
      "2018-07-14 14:49:57.208794\t日均收益率：\t0.01%\n",
      "2018-07-14 14:49:57.208794\t收益标准差：\t0.08%\n",
      "2018-07-14 14:49:57.208794\tSharpe Ratio：\t1.21\n"
     ]
    },
    {
     "data": {
      "image/png": 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W1NE/wtDme56psrC7uIIBvQ3X9IDZ7Qqb95Tw2sYi/vDre90WkG/Gt5c25o0b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\nm5EcvVC5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x183be3f9710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:59.037929\t计算回测结果\n",
      "2018-07-14 14:49:59.044920\t------------------------------\n",
      "2018-07-14 14:49:59.044920\t第一笔交易：\t2018-01-03 02:46:00\n",
      "2018-07-14 14:49:59.044920\t最后一笔交易：\t2018-06-19 20:07:00\n",
      "2018-07-14 14:49:59.044920\t总交易次数：\t79\n",
      "2018-07-14 14:49:59.044920\t总盈亏：\t1,194.52\n",
      "2018-07-14 14:49:59.044920\t最大回撤: \t-181.36\n",
      "2018-07-14 14:49:59.044920\t平均每笔盈利：\t15.12\n",
      "2018-07-14 14:49:59.044920\t平均每笔滑点：\t0.4\n",
      "2018-07-14 14:49:59.044920\t平均每笔佣金：\t18.54\n",
      "2018-07-14 14:49:59.044920\t胜率\t\t50.63%\n",
      "2018-07-14 14:49:59.044920\t盈利交易平均值\t51.68\n",
      "2018-07-14 14:49:59.044920\t亏损交易平均值\t-22.37\n",
      "2018-07-14 14:49:59.044920\t盈亏比：\t2.31\n"
     ]
    },
    {
     "data": {
      "image/png": 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vXqzq1asrJSVF8+fP16lTp5ScnKy6desqPDy84K8UQOF8/bV0//1WVwEAgNtd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\n/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spKVGOFMSCpCfG3335LQkICCoUCDw8PlEoloaGheHp6kpWVhUqlws3NjS5dupCVlUW/\nfv3o06cP3bt3Z+rUqQwYMKCzFR7J4/jl5uYSEhLC+fPn6datG3/7298MR3YZMy2OpqameHt7c+nS\nJfr27Yu5uTlff/01Wq2WkJAQunTpwo0bNwgICDCsXrQuAMZawH8tP2OmtaOXlxe5ubn07t2bc+fO\nsW7dOiwsLMjJySEmJoa0tDTCwsJE2Q9/zm/06NFkZ2cbJlNi7IcttQaaV6jeeOMNysrK2LRpE0ql\nkiFDhpCZmSn6Wgpt+0VGRpKTkyPqWqpUKvHy8iIzM5O9e/eiUCgYNmwYKSkpHDt2jMmTJ5OdnS3a\nWtpRP7H1w9Z+7u7ubNy4kfLycgD69+/PyZMnOXXqFJMmTXpk/mQ6jnE/5+kggiAQFxdHVlYWzz//\nPP/+97/JyMjg5Zdfpm/fvtTV1ZGenk5qaiq9evWisrKS2tpaQ+Pp0aNHJxs8msf1q6iooLq6GoVC\nQUxMjCgO2n7QcePGjWRlZfH2228DUFJSQmZmJu+99x4AN27cQKFQiMINpO8HbTump6fzyiuvAGBj\nY8OmTZuA5luw7t27hyAIhsfNYuuHHfFrOUZNrP1wy5YtXLlyhZkzZ+Lk5ERBQQGpqamkpqYyefJk\n9Ho9VVVVoq2lP+fX2NhIZWWlqGvp5s2byc3NZdSoUZSVlfGnP/3J8KRp5cqVHDt27L5TJYydJ/Gr\nq6sTTT980O+zzz6jsLCQ2NhY5syZw44dO/Dz86Nbt27ExcWJLn/GjCQmxAqFgpqaGsOmcW9vb159\n9VUmTJhgOAcyPDyc77//nnPnzhEREWH0e6Ja80v8xNJJ2nMcM2YMtra23Lhxg4iICExNTVmxYgUW\nFhYMHDiws8PuMFL3g/Ydn3/+eezs7PDy8sLKyoqMjAy6du3KCy+8QE5OTmeH3WF+iZ+Y++HMmTP5\n/e9/z4ULFzh//jwzZ84kOjqaXbt28cknnzBo0KDODrvDPInf4MGDAfHm0MvLi9dee42YmBjmzp1L\nVVUVKpWKwsJCbGxsGD9+vOHIUTHwS/zEkMMH/Tw9PZk1axb79+/Hx8eH06dP4+fnR0VFBebm5jz/\n/PNkZWV1dtiSQBJbJpqamrh8+TKWlpa4u7vj4uJCbm4ux44dY8SIEUDz8TLXroZ2Sm4AAALDSURB\nVF3Dzc0NLy8vXF1dOznqjiN1P2jf8ejRo4wYMYIDBw6wfft2jh8/jo+PD7NmzRKVo9T94NHtdPjw\n4cydO5e0tDR27NhBSEgIERERonKUuh+07ZiTk8Phw4dZuHAh06dPN5xJC82nK4jJUep+8LCjq6sr\nOTk5HD16lKioKF566SUyMzPZvXs34eHh9OnTR1SOT6PfTz/9xOXLl3nrrbf44osvOHr0KAkJCfTr\n14/w8HBR+Rk1gkQ4d+6csHjxYuHatWuCIAhCVVWVMHnyZKG4uNjwmYaGhs4K7xcjdT9BaN+xtrZW\nePvtt4U5c+YId+/e7eQonxyp+wnCw46VlZXC5MmTBZ1OJ2RnZwt79+4VCgoKOjnKJ0fqfoLQdjt9\n8cUXhdLSUkEQBKGxsbEzw/vFSN1PEB7dTnNzc4VDhw6Jup0+rX7V1dVCVVWVcOLECeHOnTudHKX0\nMN5DIR+Tvn37olQqSUxMpLS0lBs3btCrVy+6dOli+IyxH43zKKTuB207+vv7o1Kp+OCDD1i5cqWo\nb2eTuh887Jibm0uPHj0wNzfHx8eHmJgYXFxcOjvMJ0bqftB2O+3Rowd2dnYAotpu1hZS94NHt1NP\nT09Gjhwp6nb6tPqp1Wo0Gg2RkZGGy0Vkfj0UgiCdK0tKS0vZsWMHKSkpVFVV8fvf/57x48d3dli/\nGlL3g/YdBUEw2redHwep+4H026nU/UD6jlL3A+k7yn4yvzaSmhC3kJqair+/vyg20D8JUvcD6TtK\n3Q+k7yh1P5C+o9T9QPqOsp/Mr4UkJ8QyMjIyMjIyMjIyHUUye4hlZGRkZGRkZGRkngR5QiwjIyMj\nIyMjI/NUI0+IZWRkZGRkZGRknmrkCbGMjIyMjIyMjMxTjTwhlpGRkZGRkZGReaqRJ8QyMjIyMjIy\nMjJPNfKEWEZGRkZGRkZG5qnm/wEkRgz3S6/p5wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x183b0b6c160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:59.823124\t计算按日统计结果\n"
     ]
    }
   ],
   "source": [
    "atrRsiDf = runBacktesting(AtrRsiStrategy, {'symbolList':['tBTCUSD:bitfinex']} , '20180101', '20180630', 0.2, 1/1000, 1, 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Strategy_Portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "PortfolioDf = atrRsiDf+bollDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018-07-14 14:49:59.879068\t------------------------------\n",
      "2018-07-14 14:49:59.879068\t首个交易日：\t2018-01-01\n",
      "2018-07-14 14:49:59.879068\t最后交易日：\t2018-06-30\n",
      "2018-07-14 14:49:59.879068\t总交易日：\t181\n",
      "2018-07-14 14:49:59.879068\t盈利交易日\t33\n",
      "2018-07-14 14:49:59.879068\t亏损交易日：\t32\n",
      "2018-07-14 14:49:59.879068\t起始资金：\t1000000\n",
      "2018-07-14 14:49:59.879068\t结束资金：\t1,040,176.77\n",
      "2018-07-14 14:49:59.879068\t总收益率：\t4.02%\n",
      "2018-07-14 14:49:59.879068\t年化收益：\t5.33%\n",
      "2018-07-14 14:49:59.879068\t总盈亏：\t40,176.77\n",
      "2018-07-14 14:49:59.879068\t最大回撤: \t-9,374.34\n",
      "2018-07-14 14:49:59.879068\t百分比最大回撤: -0.9%\n",
      "2018-07-14 14:49:59.879068\t总手续费：\t18,452.72\n",
      "2018-07-14 14:49:59.879068\t总滑点：\t471.6\n",
      "2018-07-14 14:49:59.879068\t总成交金额：\t18,452,716.54\n",
      "2018-07-14 14:49:59.879068\t总成交笔数：\t180\n",
      "2018-07-14 14:49:59.879068\t日均盈亏：\t221.97\n",
      "2018-07-14 14:49:59.879068\t日均手续费：\t101.95\n",
      "2018-07-14 14:49:59.879068\t日均滑点：\t2.61\n",
      "2018-07-14 14:49:59.879068\t日均成交金额：\t101,948.71\n",
      "2018-07-14 14:49:59.879068\t日均成交笔数：\t0.99\n",
      "2018-07-14 14:49:59.879068\t日均收益率：\t0.02%\n",
      "2018-07-14 14:49:59.879068\t收益标准差：\t0.2%\n",
      "2018-07-14 14:49:59.879068\tSharpe Ratio：\t1.65\n"
     ]
    },
    {
     "data": {
      "image/png": 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Xr8dms5GVlcW///u/ExMTw6hRo3jkkUdaHDM/P5/i4mKGDBnCrFmz2L17N6Zp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\nQQAAAAsjDAIAAFgYYRAAAMDC/h9yHKleCOCGfwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x183b6e15e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PortfolioDf = PortfolioDf.dropna()\n",
    "\n",
    "# 创建回测引擎，并设置组合回测初始资金后，显示结果\n",
    "engine = BacktestingEngine()\n",
    "engine.setCapital(1000000)\n",
    "dfp, result = engine.calculateDailyStatistics(PortfolioDf)\n",
    "engine.showDailyResult(PortfolioDf, result)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
